Reinforcement Learning is in the middle of supervised and unsupervised learning.
Unlike unsupervised learning methods we have some form guidance supervision system but
this doesn't affect the output of our desired output predictions instead, it acts like a
feedback signal that tries to steer our policy to an optimal one,
improving with each update to collect maximum cumulative reward.[1]}
